It is generally known that extracting cores from oil exploration boreholes is a routine way of sampling and assessing hydrocarbon reservoirs. Borehole cores provide a unique inside into lithology and mineralogy of the subsurface. However, as a general disadvantage of the conventional techniques for investigating borehole cores, the acquisition of data is extremely costly and time consuming. Conventionally, collected cores routinely undergo multiple analyses aimed at describing the mineral composition and petrophysical (rock physics) properties of the rocks. To this end, a series of sub-samples are taken from the core and analyzed with chemical or physical procedures. As a main disadvantage, these sub-sampling procedures and analysis commonly damage or destroy the core material. Furthermore, they provide properties of the core at single positions only, but they do not allow a continuous mapping of the core material or a precise prediction of material properties, like e.g. the material composition or distribution of sample components. Thus, the amount of data that potentially could be retrieved is substantially constrained with the conventional techniques.
Various approaches for spectroscopic investigations of geological samples are known from practice. As an example, the geological sample can be analyzed using a hand-held spectrometer, which provides e.g. reflectivity spectra of a sample's surface at selected measurement positions. Again, this measurement provides information with regard to a few points only, but not a complete image of the sample composition. The amount of spectroscopic data can be increased if the hand-held spectrometer is replaced by an interferometric set-up as described e.g. in WO 2011/078869 A1, U.S. Pat. No. 4,587,424 or US 2012/0250017 A1. However, the use of a scanning interferometer represents a disadvantage in terms of the complexity of the interferometer and the operation thereof as well as with regard to the complex processing of the interferometric spectral data.
Another conventional approach for analyzing geological samples is based on hyperspectral imaging, as described e.g. by T. H. Kurz, S. J. Buckley et al. (“Close-range hyperspectral imaging for geological field studies: workflow and methods” in “International Journal of Remote Sensing” volume 34(5), issue 134, 2013, pp. 1798-1822). The hyperspectral imaging technique is based on the use of absorption characteristics of light to classify the mineralogy of a reflective surface, typically in the near infra-red part of the electromagnetic spectrum. The chemical composition and crystal structure of an object controls how light is reflected and absorbed, giving rise to unique diagnostic features that can be used to identify individual minerals.
With the conventional terrestrial application of hyperspectral imaging, a geological formation, like a cliff section or a surface mining is investigated. A hyperspectral camera having a line-shaped field of view is panned (or: rotated) for collecting a panorama image of the geological formation. Simultaneously, a topological representation is collected with a laser scanner. The hyperspectral image and the topological representation are registered for assigning spectroscopic features to certain surface ranges of geological formation.
Up to now, the hyperspectral imaging is restricted to remote sensing at terrestrial geological formations only. The conventional approach has disadvantages due to a restricted spatial resolution and a limited capability of determining the presence of different materials. Different rock types within a geological formation can be sensed, but an analysis of the rock composition was excluded with the conventional techniques. Furthermore, the practical application of the hyperspectral imaging technique may result in substantial imaging artifacts and problems with regard to image interpretation.